Active information for user devices for improved service delivery

ABSTRACT

A data communication network includes a data communication node, an imaging device, and an information handling system. The data communication node establishes a data connection with a user equipment device. The imaging device provides image information for a coverage area associated with the data communication node. The information handling system is coupled to the data communication node and to the imaging device. The information handling system receives the image information, synthesizes a 3D map of the coverage area based upon the image information, receives first coverage information from the first data communication node, correlates the first coverage information with the 3D map to generate a coverage map of the coverage area, to generate a first connectivity pattern associating a quality of connectivity provided by the first data communication node within the coverage area, and determines a first location of the first user equipment device within the connectivity pattern based on the image information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation-in-part of U.S. patent applicationSer. No. 17/711,531 entitled “REAL-TIME 3D LOCATION SERVICE FORDETERMINISTIC RF SIGNAL DELIVERY,” filed Apr. 1, 2022 and U.S. patentapplication Ser. No. 17/711,577 entitled “REAL-TIME 3D TOPOLOGY MAPPINGFOR DETERMINISTIC RF SIGNAL DELIVERY,” filed Apr. 1, 2022, thedisclosure of which is hereby expressly incorporated by reference in itsentirety.

Related subject matter is contained in co-pending U.S. patentapplication Ser. No. 18/______ (DC-131940) entitled “PRECISE POSITIONINGSYSTEM FOR INDOOR GPS ANDS RF COMPROMISED ENVIRONMENT MAPPING,” filed ofeven date herewith, the disclosure of which is hereby incorporated byreference.

FIELD OF THE DISCLOSURE

This disclosure generally relates to communication systems, and moreparticularly relates to providing active information for user devicesfor improved service delivery in a data communication network.

BACKGROUND

As the value and use of information continues to increase, individualsand businesses seek additional ways to process and store information.One option is an information handling system. An information handlingsystem generally processes, compiles, stores, and/or communicatesinformation or data for business, personal, or other purposes. Becausetechnology and information handling needs and requirements may varybetween different applications, information handling systems may alsovary regarding what information is handled, how the information ishandled, how much information is processed, stored, or communicated, andhow quickly and efficiently the information may be processed, stored, orcommunicated. The variations in information handling systems allow forinformation handling systems to be general or configured for a specificuser or specific use such as financial transaction processing,reservations, enterprise data storage, or global communications. Inaddition, information handling systems may include a variety of hardwareand software resources that may be configured to process, store, andcommunicate information and may include one or more computer systems,data storage systems, and networking systems.

SUMMARY

A data communication network may include a data communication node, animaging device, and an information handling system. The datacommunication node may establish a data connection with a user equipmentdevice. The imaging device may provide image information for a coveragearea associated with the data communication node. The informationhandling system may be coupled to the data communication node and to theimaging device. The information handling system may receive the imageinformation, synthesize a 3D map of the coverage area based upon theimage information, receive first coverage information from the firstdata communication node, correlate the first coverage information withthe 3D map to generate a coverage map of the coverage area, to generatea first connectivity pattern associating a quality of connectivityprovided by the first data communication node within the coverage area,and determine a first location of the first user equipment device withinthe connectivity pattern based on the image information.

BRIEF DESCRIPTION OF THE DRAWINGS

It will be appreciated that for simplicity and clarity of illustration,elements illustrated in the Figures have not necessarily been drawn toscale. For example, the dimensions of some of the elements areexaggerated relative to other elements. Embodiments incorporatingteachings of the present disclosure are shown and described with respectto the drawings presented herein, in which:

FIG. 1 is a block diagram illustrating a data communication networkaccording to an embodiment of the current disclosure;

FIG. 2 is a block diagram illustrating a cluster controller of the datacommunication network of FIG. 1 ;

FIG. 3 is a block diagram illustrating a generalized informationhandling system according to another embodiment of the presentdisclosure;

FIG. 4 is a block diagram of a data communication network according toanother embodiment of the current disclosure; and

FIG. 5 illustrates a portion of the data communication network of FIG. 4.

The use of the same reference symbols in different drawings indicatessimilar or identical items.

DETAILED DESCRIPTION OF DRAWINGS

The following description in combination with the Figures is provided toassist in understanding the teachings disclosed herein. The followingdiscussion will focus on specific implementations and embodiments of theteachings. This focus is provided to assist in describing the teachings,and should not be interpreted as a limitation on the scope orapplicability of the teachings. However, other teachings can certainlybe used in this application. The teachings can also be used in otherapplications, and with several different types of architectures, such asdistributed computing architectures, client/server architectures, ormiddleware server architectures and associated resources.

FIG. 1 illustrates a data communication network 100, including a clustercontroller 110, one or more data communication nodes 120, and one ormore imaging devices 130. Data communication network 100 represents adistributed communication network, such as a cellular network forcommunicating with a distributed set of user equipment (UE) 160. Forexample, data communication network 100 may represent a fifth generation(5G) cellular network, a WiFi network, a wireless Wide Area Network(WAN), another type of data communication network, or the like. UE 160may represent 5G enabled mobile cellular devices, Internet-of-Things(IoT) devices, machine-to-machine interconnected devices, or the like.In a particular embodiment data communication nodes 120 representcellular communication nodes, and may be operated, managed, andmaintained in conformance with a particular cellular infrastructurestandard, such as the Common Public Radio Interface (CPRI) standard,where the data communication nodes include Radio Equipment (RE)components configured to provide wireless data communications inaccordance with a particular wireless data protocol, and Radio EquipmentControl (REC) components configured to control the RE and to provideconnectivity to the broader cellular data network infrastructure.

The details of data communication over a data communication network, andparticularly the wireless communication over, for example, a cellulardata communication network are known in the art and will not bedescribed further herein, except as needed to illustrate the currentembodiments. UE 160 may represent any device that is configured tocommunicate within data communication network 100, and particularly withnodes 120. For example, UE 160 may include a cell phone, a tabletdevice, a computer device such as a laptop computer or a desktopcomputer, a mobile device such as a vehicle-based communication system,an IoT device, or the like.

Nodes 120 are each connected to cluster controller 110. Here, clustercontroller 110 operates to provide monitoring, management, andmaintenance services to nodes 120, as needed or desired. Clustercontroller 110 may be understood to be provided at a location that isproximate to nodes 120, or may be understood to be provided at a centrallocation for data communication network 100, such as a data centerassociated with the data communication network, and the functions andfeatures of the cluster controller may be performed by a single commoninformation handling system, or by one or more distributed informationhandling systems, as needed or desired. The monitoring, management, andmaintenance of data communication networks are known in the art and willnot be described further herein, except as needed to illustrate thecurrent embodiments.

Data communication network 100 is configured such that one or more ofnodes 120 include integrated or stand-alone imaging devices 130. Datacommunication network 100 is further configured to include one or moreadditional imaging device 130 that are not directly associated with aparticular node, but operate in a stand-alone capacity. Whetherassociated with a node, or operating as a stand-alone device, imagingdevices 130 represent devices that are located and configured to providestill picture and video monitoring of a RF coverage area of datacommunication network 100. Imaging devices 130 may include visual lightdetection devices, invisible light detection devices such as infraredcameras, lidar systems, and the like, radar imaging devices, or thelike, sound imaging devices, or other types of devices which may beutilized to generate topological information, as described below. Ineither case, cluster controller 110 operates to provide monitoring,management, and maintenance services to imaging devices 130, as neededor desired.

In a particular embodiment, cluster controller 110 operates to receiveimage information from the field of view of imaging devices 130, and RFcoverage information from nodes 120. Cluster controller 110 utilizes theimage information and the RF coverage information to synthesize a 3D mapof the physical topology of the RF coverage area of data communicationnetwork 100. Cluster controller 110 then correlates the connectionstatus for nodes 120 with the various components of UE 160 that areconnected to data communication network 100 within the field of view ofeach of the imaging devices with the 3D map of the physical topology ofthe RF coverage area. In particular, cluster controller 110 determineswhen a particular component of UE 160 experiences a diminished ordropped connection, and correlates the locations where the UEexperiences the diminished or dropped connections with the 3D map of thephysical topology of the RF coverage area. In this way, clustercontroller 110 operates to identify features 150 within the 3D map ofthe physical topology of the RF coverage area that may attenuate orblock the connection between a particular node 120 and UE 160.

For example, cluster controller 110 may operate to determine that aparticular node 120 has no current connections with an UE 160, and tocorrelate the image information provided by imaging devices 130 withinthe RF coverage area of that node, including any imaging deviceassociated with the node and any imaging device that is a stand-aloneimaging device that has a field of view that covers the RF coverage areaof the node. In this way, cluster controller 110 can synthesize a 3D mapof the RF coverage area of each of nodes 120 into a 3D map of features150 within the RF coverage area of data communication network 100.

When a particular component of UE 160 is connected to particular node120, such a connection will be maintained by the node until such time asthe connection is interrupted, for example by the UE moving out of rangeof the node or entering a coverage dead zone for the node. However,nodes 120 typically are not aware of when a connection is lost, and whena component of UE 160 loses coverage, the UE will typically initiate aprocess to initiate other connection options with a first node 120, orto establish a new connection with another node 120. That is, theconnection of UE 160 with nodes 120 is typically reactive from theperspective of the nodes. However, such a reactive approach may lead topoor performance from the perspective of UE 160 due to the poor linkperformance between the detection of the loss of connection with a firstnode 120 and the establishment of a new connection with a second node120.

In establishing and maintaining the connection between a node 120 and acomponent of UE 160, a typical node in a data communication network willprovide the communication signals to the UE utilizing amultiple-input/multiple-output (MIMO) antenna array, and will attempt toprovide the communication signals by beamforming the signals with theantenna array to maximize the received signal strength by the UE whilealso minimizing the power output of the communication signal by thenode. A node may employ various algorithms, along with feedback from theUE to shift the beamforming activities to maintain an optimal signalbetween the node and the UE. The details of establishing, maintaining,and optimizing data communication connections between nodes of a datacommunication network and the UE within the data communication networkare known in the art and will not be described further herein, except asneeded to illustrate the current embodiments.

In a particular embodiment, cluster controller 110 operates to correlatethe image information from imaging devices 130 with the beamforminginformation from nodes 120 to identify and manage the targets of theconnections between the nodes and the various UE 160 within the RFcoverage area of the nodes and data communication network 100. Clustercontroller 110 further utilizes motion information to predict the futuremotion of UE 160 within data communication network 100.

Cluster controller 110 operates to proactively direct the node 120associated with a particular component of UE 160 to provide beamformingparameters to improve the communication signal to the UE and to improvethe efficiency of the node in delivering communication signals to theUE. Moreover, utilizing the 3D map of the RF coverage areas of nodes120, cluster controller 110 operates to predict when a component of UE160 will enter a particular node's dead or highly attenuated zone, andto proactively hand off communications with that UE by another node thathas a suitable RF path to that UE. In this way, degradation inconnectivity between the components of UE 160 and data communicationnetwork 100 can be improved, and the user may not experience disruptionsin coverage, as data communication network 100 actively manages theconnections between nodes 120 and UE 160 by altering the beamformingparameters.

In another embodiment, cluster controller 110 operates to proactivelyallocate data bandwidth between nodes 120 based upon spatial insightsfrom the visual information. For example, if the RF coverage area of aparticular node 120 is seen to be sparsely populated with UE 160, andanother node is seen to be heavily populated with UE, cluster controller110 can operate to allocate more data bandwidth to the heavily populatednode if there remains a line of sight to direct the RF beam to the UEsassociated with the heavily populated node. Moreover, based uponhistorical information, future bandwidth may be prepared for other nodes120 within data communication network 100. For example, consider anevent venue that is emptying out after an event. It may be understoodthat the UE 160 associated with the event-goers may be expected to movefrom the event venue to nearby parking structures and on to adjacentroadways, and cluster controller 110 can operate to shift the backenddata bandwidth to the core network between the associated nodes 120 nearthe venue, the parking structures, and the adjacent roadways to meet theanticipated usage pattern. In another embodiment, cluster controller 110operates to correlate the users' of particular UE 160 with theirassociated service level agreements (SLAs), and to allocate databandwidth with the UE accordingly.

In a particular embodiment, cluster controller 110 utilizes artificialintelligence/machine learning (AI/ML) algorithms to analyze the imageinformation to monitor and maintain the 3D map. For example, whilefeatures 150 may typically be understood to represent fixed features,such as buildings or other fixed signal obstructions, utilizing AI/MLalgorithms, cluster controller 110 may add real-time RF pathobstructions to the 3D map of the RF coverage area of nodes 120.Consider a large mobile obstruction, such as a bus or large truck,moving through a particular node's 120 RF coverage area. Clustercontroller 110 may operate to improve the real-time maintenance ofconnectivity, such as dead zone detection, rapidly changing RFenvironment, and beamforming activities, to better account for themobile obstruction to the RF paths. It may be further understood thatother real-time RF path obstructions may be identified, such as humanbodies or animals within the 3D map. Further, utilizing the AI/MLalgorithms, cluster controller 110 can operate to predict processingneeds for the RF coverage area of nodes 120, and increase or decreasebackend processing capacity to meet the changing demand profile.

As described herein, the functions and features of cluster controller110 may instantiated in hardware, in software or code, or in acombination of hardware and code configured to perform the describedfunctions and features. Moreover, the functions and features may beprovided at a single location or by a single device, such as aninformation handling system, or may be provided at two or more locationsby two or more devices, such as by two or more information handlingsystems. One or more of the functions and features as described hereinmay be each performed by a different information handling system, andany particular function or feature may be distributed across two or moreinformation handling systems, as needed or desired. Further, asdescribed herein, the functions and features of cluster controller 110may be understood to be provided at any network level as needed ordesired.

For example, where data communication network 100 includes separategroups of nodes 120, where each group of nodes is routed through acommon access switch, where the data flows from separate groups ofaccess switches are aggregated by a common aggregator, where theprocessing demands of groups of aggregators are processed by a core dataprocessing network, then the functions and features of clustercontroller 110 may provided by one or more of the access switches, theaggregators, or the core network, as needed or desired. As such, it maybe deemed desirable to perform map synthesis at the core network, whereaccess times are typically longer, but data processing capacities aretypically greater, whereas it may be deemed desirable to perform UEmotion tracking and connection hand-offs at a processing level that iscloser to the nodes, where access times are typically shorter.

FIG. 2 illustrates cluster controller 110 in greater detail. Clustercontroller 110 is configured to receive imaging inputs 210 from imagingdevices 130. Cluster controller 110 operates to process the imaginginputs and to control the operations of nodes in data communicationnetwork 100 including nodes 120. Cluster controller 110 further operatesto provide the nodes with pre-configurations 230, resource tracking 232of UEs within data communication network 100 including UE 160, and RFpower management 234 for the nodes.

Imaging inputs 210 represent the output from imaging devices 130, andmay include any still or motion imaging format as may be known in theart, including proprietary still or motion imaging formats. Where aparticular imaging device 130 is configured to still images (that is, acamera device), the images will be understood to be received by clustercontroller based upon various time stamps (t0, t1, t2, . . . ) that areassociated with a real-time at which the still images were captured.Still image imaging devices 130 may be configured to capture images on apredetermined time schedule, such as once every five or ten seconds, ormay be configured to capture images based upon various inputs to theimaging device, such as based upon a motion sensor or the like. Videoimage imaging devices may be configured to provide continuous streamvideo images or may be configured to provide video images based upon thevarious time stamps (t0, t1, t2, . . . ). Imaging devices 130 may beconfigured to capture images within the visible light spectrum, withinthe near-visible light spectrum, or at other non-visible light spectrumsas needed or desired.

Cluster controller 110 includes a map synthesis module 220, a motionprediction module 222, a dead zone prediction module 224, a RF coveragemap module 226, and an optimization/learning module 228. Map synthesismodule 220 receives imaging inputs 210 and synthesizes a 3D map of theRF coverage area of data communication network 100 as described above.Here it will be understood that inputs from two or more imaging devices130 will be utilized to synthesize the 3D map of the RF coverage area ofdata communication network 100, and that the more imaging device inputsthat are received by cluster controller 110, the better and moreaccurate will be the 3D map synthesized by map synthesis module 220.Cluster controller 110 further receives coverage information from nodes120. For example, cluster controller 110 may receive RF signal intensitymaps 226 for the RF coverage areas associated with each node 120,including default beamforming settings, coverage angles, RF signal powersettings, and the like. Here, dead zone prediction module 224 operatesto correlate the synthesized 3D map with the received coverageinformation to generate a baseline RF coverage map that predicts thepresence of features 150 that are understood to present obstacles thatattenuate the RF signals between nodes 120 and UE 160.

In a particular embodiment, the baseline RF coverage map is synthesizedbased upon real-time information from imaging devices 130. Inparticular, it will be understood that a particular RF coverage area fora particular node 120 may be constantly populated by one or more UE 160,and other objects within the field of view of imaging devices 130 thatmay make the generation of the baseline RF coverage map difficult.However, here, map synthesis module 220 may utilizeoptimization/learning module 228 to create the baseline RF coverage mapfor the hypothetical situation where the RF coverage area is empty ofUEs 160 and other objects based upon learned responses from the RFcoverage area. Further, map synthesis module 220 operates toperiodically update the baseline RF coverage map based upon the changingconditions within the RF coverage area. For example, where a RF coveragearea represents an event venue, the presence of moving vans in a loadingarea may represent temporary obstructions within the coverage area ofnodes 120 within line of sight of the loading area. Or, where a RFcoverage area represents an office space, a reorganization of cubicleswithin the office space may militate for an updated coverage map for theoffice area.

Cluster controller 110 further utilizes artificial intelligence/machinelearning (AI/ML) algorithms embodied in optimization/learning module 228to analyze the image information to monitor and maintain the baseline RFcoverage map. For example, while features 150 may typically beunderstood to represent fixed or semi-permanent features, such asbuildings, parked vehicles, or other fixed signal obstructions,utilizing AI/ML algorithms, cluster controller 110 may add real-time RFpath obstructions to the baseline RF coverage map of the RF coveragearea of nodes 120. Consider a large mobile obstruction, such as a bus orlarge truck, moving through a particular node's 120 RF coverage area.Cluster controller 110 may operate to improve the real-time maintenanceof connectivity, such as dead zone detection, rapidly changing RFenvironment, and beamforming activities, to better account for themobile obstruction to the RF paths. Further, utilizing the AI/MLalgorithms, cluster controller 110 can operate to predict processingneeds for the RF coverage area of nodes 120, and increase or decreasebackend processing capacity to meet the changing demand profile.

This baseline RF coverage map can be utilized in conjunction with themotion of objects within the RF coverage area as determined by motionprediction module 222. As such the movement of vehicles, people, and thelike, through the RF coverage area can be predicted. Movement detectionmodule 222 further operates to identify the speed and trajectory of theobjects, and can thereby distinguish between people and vehicles orother objects within the RF coverage area. Then, based upon the mapinformation from map synthesis module 220 and the object and motioninformation from object detection module 222, dead zone predictionmodule 224 operates to predict coverage dead zones for each of nodes120. The dead zones can be combined with information from apre-determined RF coverage map module 226 to predict the real-time deadzones for each of nodes 120.

Returning to motion prediction module 222, the movement of objectsthrough the RF coverage areas of nodes 120 is combined with informationrelated to each node's beamforming status for the UEs 160 in the RFcoverage area. Motion prediction module 222 further operates to identifyobjects that are within the RF coverage area of each node 120 that areassociated with users of UE 160, and the users' speed and trajectory.Dead zone prediction module 224 further operates to correlate themovements of UEs 160 with the identified dead zones to determine inadvance when a particular UE is expected to lose connection with aparticular node 120, and further operates to determine a next best nodeto pass the UE to. Optimization/learning module 228 utilizes variousAI/ML algorithms to better predict the emergence of signal blockingobstructions and the expected motions of the users of the connected UEs160. Cluster controller 110 finally operates to direct the activities ofnodes 120 to proactively maintain an optimum connection status for theUEs within the RF coverage area of data communication network 100,through the implementation of pre-configurations 230, UE resourcetracking 232, and RF power management of the nodes, as described above.

FIG. 4 illustrates a data communication network 400 similar to datacommunication network 100. Data communication network 400 provides a RFcoverage area for a structure, such as an office building, a shoppingmall, an apartment building, a home or other dwelling, or other type ofenvironment that can be characterized as inhabiting a 3D volume. Assuch, data communication network 400 provides the RF coverage area for afirst floor 410, a second floor 420, and a third floor 430. First floor410 includes data communication nodes/imaging devices 412 and 414,second floor 420 includes data communication nodes/imaging devices 422and 424, and third floor 430 includes data communication nodes/imagingdevices 432 and 434. Data communication nodes/imaging devices 412, 414,422, 424, 432, and 434 (hereinafter referred to as “nodes”) representdata communication and imaging devices that combine the functions andfeatures of nodes 120 and imaging devices 130, as described above. Nodes412, 414, 422, 424, 432, and 434 are each connected to a clustercontroller 440 similar to cluster controller 110, as described above.

Nodes 412 and 414 provide network connectivity and imaging dataprimarily for UEs on first floor 410, nodes 422 and 424 provide networkconnectivity and imaging data primarily for UEs on second floor 420, andnodes 432 and 434 provide network connectivity and imaging dataprimarily for UEs on third floor 430. Thus while not strictly precluded,network connectivity provided to UEs outside the bounds of theirrespective floors is incidental to the teachings of the currentdisclosure, and therefore will not be discussed further unless otherwiseneeded to illustrate the current embodiments. In addition to nodes 412and 414, first floor 410 may include one or more additional nodes, oneor more additional stand-alone data communication devices, and one ormore additional stand-alone imaging devices, as needed or desired.Similarly, second floor 420 and third floor 430 may include one or moreadditional nodes, one or more additional stand-alone data communicationdevices, and one or more additional stand-alone imaging devices, asneeded or desired. The teachings of the current disclosure with respectto FIGS. 1 and 2 , as described above, may be incorporated into datacommunication network 400 unless otherwise described herein, and theteachings related to data communication network 400 may be able to beincorporated into data communication network 100, as needed or desired.

It has been understood by the inventors of the current disclosure thatwireless communication technologies are rapidly being integrated intobusinesses, residences, retail spaces, event venues, and the like.Further, the need for positioning information for the UEs within suchlocations is increasing in order to provide richer user environments.However, such locations may typically be characterized as beingGPS-compromised, or as being otherwise lacking in precise positioningcapabilities. It has been further understood that precise positioning inindoor or other GPS-compromised environments typically requires the useof separate beacons added to the environments, or the use ofmilitary-grade GPS devices, both of which unduly add to the cost ofdeployment to the data communication network.

Data communication network 400 utilizes cluster controller 440 toreceive image data from nodes 412, 414, 422, 424, 432, and 434, alongwith the RF coverage map from the nodes to provide a precise 3D map ofthe physical topology of the RF coverage area of the data communicationnetwork. Due to the segregated nature of the image information fromfirst floor 410, from second floor 420, and from third floor 430, the 3Dmap can easily distinguish between a UE on the first floor (UE1), a UEon the second floor (UE2), and a UE on the third floor (UE3).

Data communication network 400 is illustrated as being oriented withrespect to a 3D coordinate system 450. In this regard, UE1 can belocated in coordinate system 450 at a location 451 by nodes 412 and 414,UE2 can be located in the coordinate system at a location 452 by nodes422 and 424, and UE3 can be located in the coordinate system at alocation 453 by nodes 432 and 434. In this way, precise locationinformation can be provided for UEs within the RF coverage area,including height information, as needed or desired. In particular, theuse of multiple nodes, and especially the imaging device portions of thenodes, permits the imaging information to provide the 3D map, includingthe precise location information and the height information.

As depicted in FIG. 4 , data communication network 400 provides a RFcoverage area within a confined space, such as within a building, butthis is not necessarily so. In particular, the teachings of the currentdisclosure are amenable to providing precise location information forUEs within the RF coverage area for other types of locations. Forexample, a shopping mall may have one or more large open spaces, suchthat the imaging devices provide image information for more than onefloor. The 3D map of the coverage area may still be utilized to provideprecise location information, including height information, as needed ordesired. In another example, a stadium environment, with no clear“floors” in the seating areas, may nevertheless provide precise locationinformation for the UEs within the stadium based upon the 3D map of thestadium, as needed or desired.

With precise location information, UEs can be provided with more preciselocation services. For example, where the RF coverage area represents amulti-floor building, such as a shopping mall, a user may query for aparticular location within the mall (for example, a store, a food court,a parking garage, etc.), and, based upon the 3D map of the mall, theuser may be provided with step-by-step directions, including floorchanges, to the desired location, as needed or desired.

The current embodiments may provide the precise location serviceswithout necessitating specialized UEs to receive high precision GPS orthe like, and without necessitating specialized nodes, as access pointsand wireless routers are increasingly being provided with integratedvideo imaging devices. Moreover, as the operating frequency of modernwireless communications increases, the number of deployed nodes isincreasing, permitting the greater utilization of the image informationto provide more detailed 3D mapping, as needed or desired.

FIG. 5 illustrates a portion of data communication network 400. Inparticular, FIG. 5 illustrates third floor 430 with nodes 432 and 434,and UE3. The X-Y surface of third floor 430 is illustrated with aconnectivity pattern for the quality of connectivity provided in variousregions of the third floor. In particular, third floor 430 isillustrated as having a first “Good Connectivity” zone close to node432, a “Fair Connectivity” zone further removed from node 432, a “PoorConnectivity” zone between node 432 and node 434, another “FairConnectivity” zone closer to node 434, and another “Good Connectivity”zone close to node 434. The connectivity zones are analogous to the“number of bars” indication for signal strength on a particular UEdevice. However, cluster controller 440 operates to correlate the“number of bars” indications from multiple UEs with the 3D map of the RFcoverage area of data communication network 400 to determine the precisebounds of the connectivity zones. The number of different levels ofconnectivity of the connectivity zones may differ from the three levelillustrated here (that is, good, fair, and poor), as needed or desired.The indications of signal quality may include Received Signal StrengthIndications (RSSI) or other indications, as may be known in the art.

It has been understood by the inventors of the current disclosure thatthe a user's typical options for finding better signal coverage arelimited to wandering around, looking at the user's UE to see when the“number of bars” indicator increases, and stopping in the spot with themost bars.

In a particular embodiment, UEs interact with data communication network400 to receive near real time indications as to where to find bettersignal strength based upon the 3D map of the RF coverage area, and theassociated connectivity pattern for the quality of connectivity providedin various regions of the RF coverage area. Thus, for example, UE3,finding itself in the “Poor Connectivity” zone, receives a directionindication to move toward one of the “Good Connectivity” zonesassociated with node 432 and 434. In a simple space, such as a room, thedirection indication may include a compass-pointer type indicationpointing to the “Good Connectivity” zones. In a more complex space, suchas a floor of office cubicles, the direction indication may includeturn-by-turn directions to the “Good Connectivity” zone.

The current embodiment is illustrated with respect to a particular floorin a building, but this is not necessarily so. In particular, directionindications can be provided for indoor spaces, outdoor spaces, or mixedspaces, as needed or desired. In a particular example, a RF coveragezone may include a park and various adjacent businesses that includeaccess points associated with the data communication network. The parkarea may have poorer connectivity, but a nearby business with an accesspoint may provide improved connectivity. In this case, the UE can beprovided with an indication such as “Proceed to business X for improvedconnectivity.” Further, the direction indications may be visualindications, audio indications, haptic indications, or the like.

In a particular embodiment, data communication network 400 incorporatesbandwidth utilization information in the determination of the directionindications. For example, third floor 430 is illustrated as having alarger number of UEs proximate to node 434. While both node 432 and node434 are both associated with their own “Good Connectivity” zones,cluster controller 440 operates to determine that the availablebandwidth on node 432 is greater than on node 434. In this case, clustercontroller 440 operates to direct UE3 to the “Good Connectivity” zoneassociated with node 432.

It has been further understood by the inventors of the currentdisclosure that the indications received by UEs within the RF coveragearea may vary with time, due to dynamic interactions with thesurrounding environment, bandwidth usage between other UEs within the RFcoverage area and the nodes, and other factors. Thus, in a particularembodiment, UEs within an RF coverage area operate to provide thecurrent status of their signal strength indications. In this case,cluster controller 440 operates to modify the associated connectivitypattern for the quality of connectivity provided in various regions ofthe RF coverage area based upon the received signal strength indicationsto provide more real time indications as to where to find better signalstrength.

An example of rendering a 3D map of the physical topology, as describedin the various embodiments of the current disclosure, may includecorrelating multiple imaging inputs 210 utilizing a Neural Radiant Field(NeRF) algorithm, a Structure from Motion (SfM) algorithm, or the like.

FIG. 3 illustrates a generalized embodiment of an information handlingsystem 300. For purpose of this disclosure an information handlingsystem can include any instrumentality or aggregate of instrumentalitiesoperable to compute, classify, process, transmit, receive, retrieve,originate, switch, store, display, manifest, detect, record, reproduce,handle, or utilize any form of information, intelligence, or data forbusiness, scientific, control, entertainment, or other purposes. Forexample, information handling system 300 can be a personal computer, alaptop computer, a smart phone, a tablet device or other consumerelectronic device, a network server, a network storage device, a switchrouter or other network communication device, or any other suitabledevice and may vary in size, shape, performance, functionality, andprice. Further, information handling system 300 can include processingresources for executing machine-executable code, such as a centralprocessing unit (CPU), a programmable logic array (PLA), an embeddeddevice such as a System-on-a-Chip (SoC), or other control logichardware. Information handling system 300 can also include one or morecomputer-readable medium for storing machine-executable code, such assoftware or data. Additional components of information handling system300 can include one or more storage devices that can storemachine-executable code, one or more communications ports forcommunicating with external devices, and various input and output (I/O)devices, such as a keyboard, a mouse, and a video display. Informationhandling system 300 can also include one or more buses operable totransmit information between the various hardware components.

Information handling system 300 can include devices or modules thatembody one or more of the devices or modules described below, andoperates to perform one or more of the methods described below.Information handling system 300 includes a processors 302 and 304, aninput/output (I/O) interface 310, memories 320 and 325, a graphicsinterface 330, a basic input and output system/universal extensiblefirmware interface (BIOS/UEFI) module 340, a disk controller 350, a harddisk drive (HDD) 354, an optical disk drive (ODD) 356, a disk emulator360 connected to an external solid state drive (SSD) 364, an I/O bridge370, one or more add-on resources 374, a trusted platform module (TPM)376, a network interface 380, a management device 390, and a powersupply 395. Processors 302 and 304, I/O interface 310, memory 320 and325, graphics interface 330, BIOS/UEFI module 340, disk controller 350,HDD 354, ODD 356, disk emulator 360, SSD 364, I/O bridge 370, add-onresources 374, TPM 376, and network interface 380 operate together toprovide a host environment of information handling system 300 thatoperates to provide the data processing functionality of the informationhandling system. The host environment operates to executemachine-executable code, including platform BIOS/UEFI code, devicefirmware, operating system code, applications, programs, and the like,to perform the data processing tasks associated with informationhandling system 300.

In the host environment, processor 302 is connected to I/O interface 310via processor interface 306, and processor 304 is connected to the I/Ointerface via processor interface 308. Memory 320 is connected toprocessor 302 via a memory interface 322. Memory 325 is connected toprocessor 304 via a memory interface 327. Graphics interface 330 isconnected to I/O interface 310 via a graphics interface 332, andprovides a video display output 335 to a video display 334. In aparticular embodiment, information handling system 300 includes separatememories that are dedicated to each of processors 302 and 304 viaseparate memory interfaces. An example of memories 320 and 325 includerandom access memory (RAM) such as static RAM (SRAM), dynamic RAM(DRAM), non-volatile RAM (NV-RAM), or the like, read only memory (ROM),another type of memory, or a combination thereof.

BIOS/UEFI module 340, disk controller 350, and I/O bridge 370 areconnected to I/O interface 310 via an I/O channel 312. An example of I/Ochannel 312 includes a Peripheral Component Interconnect (PCI)interface, a PCI-Extended (PCI-X) interface, a high-speed PCI-Express(PCIe) interface, another industry standard or proprietary communicationinterface, or a combination thereof. I/O interface 310 can also includeone or more other I/O interfaces, including an Industry StandardArchitecture (ISA) interface, a Small Computer Serial Interface (SCSI)interface, an Inter-Integrated Circuit (I2C) interface, a System PacketInterface (SPI), a Universal Serial Bus (USB), another interface, or acombination thereof. BIOS/UEFI module 340 includes BIOS/UEFI codeoperable to detect resources within information handling system 300, toprovide drivers for the resources, initialize the resources, and accessthe resources. BIOS/UEFI module 340 includes code that operates todetect resources within information handling system 300, to providedrivers for the resources, to initialize the resources, and to accessthe resources.

Disk controller 350 includes a disk interface 352 that connects the diskcontroller to HDD 354, to ODD 356, and to disk emulator 360. An exampleof disk interface 352 includes an Integrated Drive Electronics (IDE)interface, an Advanced Technology Attachment (ATA) such as a parallelATA (PATA) interface or a serial ATA (SATA) interface, a SCSI interface,a USB interface, a proprietary interface, or a combination thereof. Diskemulator 360 permits SSD 364 to be connected to information handlingsystem 300 via an external interface 362. An example of externalinterface 362 includes a USB interface, an IEEE 1394 (Firewire)interface, a proprietary interface, or a combination thereof.Alternatively, solid-state drive 364 can be disposed within informationhandling system 300.

I/O bridge 370 includes a peripheral interface 372 that connects the I/Obridge to add-on resource 374, to TPM 376, and to network interface 380.Peripheral interface 372 can be the same type of interface as I/Ochannel 312, or can be a different type of interface. As such, I/Obridge 370 extends the capacity of I/O channel 312 when peripheralinterface 372 and the I/O channel are of the same type, and the I/Obridge translates information from a format suitable to the I/O channelto a format suitable to the peripheral channel 372 when they are of adifferent type. Add-on resource 374 can include a data storage system,an additional graphics interface, a network interface card (NIC), asound/video processing card, another add-on resource, or a combinationthereof. Add-on resource 374 can be on a main circuit board, on separatecircuit board or add-in card disposed within information handling system300, a device that is external to the information handling system, or acombination thereof.

Network interface 380 represents a NIC disposed within informationhandling system 300, on a main circuit board of the information handlingsystem, integrated onto another component such as I/O interface 310, inanother suitable location, or a combination thereof. Network interfacedevice 380 includes network channels 382 and 384 that provide interfacesto devices that are external to information handling system 300. In aparticular embodiment, network channels 382 and 384 are of a differenttype than peripheral channel 372 and network interface 380 translatesinformation from a format suitable to the peripheral channel to a formatsuitable to external devices. An example of network channels 382 and 384includes InfiniBand channels, Fibre Channel channels, Gigabit Ethernetchannels, proprietary channel architectures, or a combination thereof.Network channels 382 and 384 can be connected to external networkresources (not illustrated). The network resource can include anotherinformation handling system, a data storage system, another network, agrid management system, another suitable resource, or a combinationthereof.

Management device 390 represents one or more processing devices, such asa dedicated baseboard management controller (BMC) System-on-a-Chip (SoC)device, one or more associated memory devices, one or more networkinterface devices, a complex programmable logic device (CPLD), and thelike, that operate together to provide the management environment forinformation handling system 300. In particular, management device 390 isconnected to various components of the host environment via variousinternal communication interfaces, such as a Low Pin Count (LPC)interface, an Inter-Integrated-Circuit (I2C) interface, a PCIeinterface, or the like, to provide an out-of-band (00B) mechanism toretrieve information related to the operation of the host environment,to provide BIOS/UEFI or system firmware updates, to managenon-processing components of information handling system 300, such assystem cooling fans and power supplies. Management device 390 caninclude a network connection to an external management system, and themanagement device can communicate with the management system to reportstatus information for information handling system 300, to receiveBIOS/UEFI or system firmware updates, or to perform other task formanaging and controlling the operation of information handling system300. Management device 390 can operate off of a separate power planefrom the components of the host environment so that the managementdevice receives power to manage information handling system 300 when theinformation handling system is otherwise shut down. An example ofmanagement device 390 include a commercially available BMC product orother device that operates in accordance with an Intelligent PlatformManagement Initiative (IPMI) specification, a Web Services Management(WSMan) interface, a Redfish Application Programming Interface (API),another Distributed Management Task Force (DMTF), or other managementstandard, and can include an Integrated Dell Remote Access Controller(iDRAC), an Embedded Controller (EC), or the like. Management device 390may further include associated memory devices, logic devices, securitydevices, or the like, as needed or desired.

Although only a few exemplary embodiments have been described in detailherein, those skilled in the art will readily appreciate that manymodifications are possible in the exemplary embodiments withoutmaterially departing from the novel teachings and advantages of theembodiments of the present disclosure. Accordingly, all suchmodifications are intended to be included within the scope of theembodiments of the present disclosure as defined in the followingclaims. In the claims, means-plus-function clauses are intended to coverthe structures described herein as performing the recited function andnot only structural equivalents, but also equivalent structures.

The above-disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover any andall such modifications, enhancements, and other embodiments that fallwithin the scope of the present invention. Thus, to the maximum extentallowed by law, the scope of the present invention is to be determinedby the broadest permissible interpretation of the following claims andtheir equivalents, and shall not be restricted or limited by theforegoing detailed description.

What is claimed is:
 1. A data communication network, comprising: a firstdata communication node configured to establish a first data connectionwith a user equipment device within a coverage area of the datacommunication network; a plurality of imaging devices configured toprovide image information for the coverage area; and an informationhandling system coupled to the first data communication node and to theimaging devices, wherein the information handling system is configuredto receive the image information, to synthesize a three-dimensional (3D)map of the coverage area based upon the image information, to receivefirst coverage information from the first data communication node, tocorrelate the first coverage information with the 3D map to generate acoverage map of the coverage area, to generate a first connectivitypattern associating a quality of connectivity provided by the first datacommunication node within the coverage area, and to determine a firstlocation of the first user equipment device within the firstconnectivity pattern based on the image information.
 2. The datacommunication network of claim 1, wherein the information handlingsystem is further configured to determine that the first location isassociated with a first level of quality of connectivity.
 3. The datacommunication network of claim 2, wherein the information handlingsystem is further configured to determine that the first connectivitypattern includes a second location that is associated with a secondlevel of quality of connectivity, the second level of quality beinggreater than the first level of quality.
 4. The data communicationnetwork of claim 3, wherein the information handling system is furtherconfigured to provide directions to the user equipment device to thesecond location.
 5. The data communication network of claim 3, furthercomprising: a second data communication node; wherein the informationhandling system is further configured to generate a second connectivitypattern associating a quality of connectivity provided by the seconddata communication node within the coverage area.
 6. The datacommunication network of claim 5, wherein the information handlingsystem is further configured to determine that the second connectivitypattern includes a third location that is associated with a third levelof quality of connectivity, the third level of quality being greaterthan the first level of quality.
 7. The data communication network ofclaim 6, wherein the information handling system is further configuredto provide directions to the user equipment device to the thirdlocation, and to direct the second data communication node to establisha second data connection with the user equipment device at the thirdlocation.
 8. The data communication network of claim 7, wherein: thesecond level of quality is greater than the third level of quality; andthe information handling system is further configured to determine thata first bandwidth utilization of the first data communication node isgreater than a second bandwidth utilization of the second datacommunication node, wherein providing the directions to the userequipment device to the third location is in response to determiningthat first bandwidth utilization is greater than the second bandwidthutilization.
 9. A method, comprising: providing, in a data communicationnetwork, a first data communication node configured to establish a firstdata connection with a user equipment device within a coverage area ofthe data communication network; providing, in the data communicationnetwork, a plurality of imaging devices configured to provide imageinformation for the coverage area; and providing, in the datacommunication network, an information handling system coupled to thefirst data communication node and to the imaging devices; receiving, bythe information handling system, the image information; synthesizing athree-dimensional (3D) map of the coverage area based upon the imageinformation; receiving first coverage information from the first datacommunication node; correlating the first coverage information with the3D map to generate a coverage map of the coverage area; and generating afirst connectivity pattern associating a quality of connectivityprovided by the first data communication node within the coverage area;determining a first location of the first user equipment device withinthe connectivity pattern based on the image information.
 10. The methodof claim 9, further comprising: determining that the first location isassociated with a first level of quality of connectivity.
 11. The methodof claim 10, further comprising: determining that the first connectivitypattern includes a second location that is associated with a secondlevel of quality of connectivity, the second level of quality beinggreater than the first level of quality.
 12. The method of claim 11,further comprising: providing directions to the user equipment device tothe second location.
 13. The method of claim 11, further comprising:providing, in the data communication network, a second datacommunication node; and generating a second connectivity patternassociating a quality of connectivity provided by the second datacommunication node within the coverage area.
 14. The method of claim 13,further comprising: determining that the second connectivity patternincludes a third location that is associated with a third level ofquality of connectivity, the third level of quality being greater thanthe first level of quality.
 15. The method of claim 14, furthercomprising: provide directions to the user equipment device to the thirdlocation; and directing the second data communication node to establisha second data connection with the user equipment device at the thirdlocation.
 16. The data communication network of claim 15, wherein: thesecond level of quality is greater than the third level of quality; andthe method further comprises determining that a first bandwidthutilization of the first data communication node is greater than asecond bandwidth utilization of the second data communication node,wherein providing the directions to the user equipment device to thethird location is in response to determining that first bandwidthutilization is greater than the second bandwidth utilization.
 17. Aninformation handling system, comprising: a memory device for storingcode; and a processor configured to execute the code to: receive imageinformation from a plurality of imaging devices of a data communicationnetwork; synthesize a three-dimensional (3D) map of a coverage area ofthe data communication network based upon the image information; receivefirst coverage information for a first coverage area of the datacommunication network from a first data communication node of the datacommunication network; correlate the first coverage information with the3D map to generate a coverage map of the coverage area; generate a firstconnectivity pattern associating a quality of connectivity provided bythe first data communication node within the coverage area; anddetermine a first location of a first user equipment device within theconnectivity pattern based on the image information.
 18. The informationhandling system of claim 17, wherein the processor is further configuredto execute code to determine that the first location is associated witha first level of quality of connectivity.
 19. The information handlingsystem of claim 18, wherein the processor is further configured toexecute code to determine that the first connectivity pattern includes asecond location that is associated with a second level of quality ofconnectivity, the second level of quality being greater than the firstlevel of quality.
 20. The information handling system of claim 19,wherein the processor is further configured to execute code to providedirections to the user equipment device to the second location.